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Lead and develop a research program in microelectronics (heterojunction device physics and transport measurements); manage and support cleanroom nanofabrication tools (EBL, plasma FIB), electrical probe stations, and process development; provide technical guidance and user support for external collaborators; collaborate across CNM/Argonne and troubleshoot instrumentation to ensure reliable operation.

Conduct computational and experimental research developing AI and automated workflows to study interfacial processes in electrochemical materials. Develop and apply AI classifiers and optimization schemes, build autonomous experimental campaigns, perform electrochemical measurements and analytical characterization, adapt workflows for automation, and collaborate across interdisciplinary teams.

Serve as scientific and technical lead for a DOE-wide AI STEM Educator Jam: design AI-enabled scientific challenge frameworks, develop datasets and LLM workflows, train facilitators, support event implementation, coordinate with cross-lab teams, and iterate content based on feedback to ensure scientific integrity and accessibility.

Design, develop, and evaluate agentic AI systems for scientific discovery, integrating agents with simulations, data pipelines, instruments, workflows, and knowledge bases. Build methods for planning, memory, tool use, workflow orchestration, and decision-making. Deploy and scale systems in HPC/distributed environments, assess scientific usefulness, reliability, robustness, efficiency, and safety, and collaborate with multidisciplinary teams to advance Argonne's AI and scientific missions.

Develop, implement, and support hardware and software for synchrotron beamline control, data acquisition, and analysis. Modernize control systems using C/C++ on Linux, Python, Git, embedded controllers, ROS/EPICS, robotics, electronics, and AI/ML for automation. Translate scientific requirements into technical solutions and documentation.

Support design, development, and integration of ALCF HPC environments. Administer Linux clusters, manage software stacks with Spack, create programming environments (modules/containers), resolve dependency conflicts, maintain compilers and scientific libraries, implement CI and containerized builds, and collaborate with researchers to support scientific computing workloads. Role requires U.S. citizenship and may be filled at junior or more senior technical levels depending on experience.

Conduct research and develop post-training and reinforcement learning methods for scientific foundation models, optimize large-scale training and post-training workflows on leadership-class supercomputers, and collaborate with multidisciplinary teams to apply adaptive learning systems to high-impact scientific problems, publishing and communicating results.

Implement and sustain a CMMS and Configuration Database ecosystem for APS assets. Define asset hierarchies and baselines, integrate CMMS with engineering and operational systems, ensure data governance and configuration integrity, support change control and lifecycle documentation, and enable predictive maintenance and reliability analytics to improve asset performance.

Develop learning-enabled imaging algorithms for 3D reconstruction and real-time adaptive acquisition of noisy synchrotron datasets; implement multimodal alignment and fusion of structural, chemical, and biological signals; collaborate with scientists across computational science, physics, biology, and environmental chemistry to guide experiments and analyze data.

Develop and deploy AI/ML tools for x-ray imaging and autonomous experiments, integrate models into beamline software, build closed-loop workflows and automated pipelines, support on-site user operations, manage metadata and curated datasets, and collaborate with facility AI and computing teams to scale tools for high-throughput tomography and high-speed imaging.